|Numéro de publication||US8732004 B1|
|Type de publication||Octroi|
|Numéro de demande||US 11/231,339|
|Date de publication||20 mai 2014|
|Date de dépôt||20 sept. 2005|
|Date de priorité||22 sept. 2004|
|Numéro de publication||11231339, 231339, US 8732004 B1, US 8732004B1, US-B1-8732004, US8732004 B1, US8732004B1|
|Inventeurs||Armando Ramos, Stephen R. Meeks, Michele M. Bodda, Pamela Fielding|
|Cessionnaire d'origine||Experian Information Solutions, Inc.|
|Exporter la citation||BiBTeX, EndNote, RefMan|
|Citations de brevets (289), Citations hors brevets (100), Référencé par (18), Classifications (5), Événements juridiques (1)|
|Liens externes: USPTO, Cession USPTO, Espacenet|
This application claims the benefit of priority under 35 U.S.C. §119(e) of U.S. Provisional Application No. 60/612,313, filed on Sep. 22, 2004 and entitled AUTOMATED ANALYSIS OF CONSUMER DATA TO GENERATE PROSPECT NOTIFICATIONS BASED ON TRIGGER EVENTS, the entirety of which is incorporated herein by reference.
One embodiment of the invention relates to systems and methods for monitoring changes in a database and, in particular, for monitoring changes to a selected subset of records in the database.
Consumer credit databases, such as those maintained by companies who calculate credit scores, are typically enormous in size and are continually updated to reflect very recent consumer activity details for hundreds of millions of consumers. Many lenders, merchants, and other providers of credit-related products desire to exploit the wealth of data available in these databases. In particular, credit-providers would find it very advantageous to exploit the databases in order to improve or replace, at least in part, their blanket marketing campaigns, in which the credit-providers send out advertisements, make cold phone calls, or otherwise contact large numbers of consumers, based on general selection criteria, with offers of their credit-related products and/or services, in hopes that at least a portion of the contacted consumers will respond to their offers. Unfortunately, such blanket advertisement campaigns often reach consumers who are not eligible for the offers or who are not actively interested in extensions of credit and are therefore less motivated to seriously consider a lender's offer. Industry research indicates that less than 0.1% of contacts made in such blanket campaigns result in a sale.
Information in the consumer credit databases could help the credit-providers identify potentially interested and credit-worthy customers. However, several technical, database-related obstacles have kept credit providers from fully utilizing the potential of the information available from the consumer credit databases. For one, the consumer credit databases are typically organized and optimized for quick extraction of simple bits of information about individual consumers, such as individual credit scores, while allowing the database to continually insert incoming consumer data into its records.
Out of an abundance of caution, credit-providers often prefer to have complex, computationally-expensive, and time-consuming analyses and classifications performed on the database records as part of their identification of prospective customers, in an effort to avoid making the firm offer of credit that is mandated by the Fair Credit Reporting Act (FCRA) to consumers who may later in the process be revealed as being undesirable credit risks.
Furthermore, even if a solution could be found to reconcile the conflicting needs for a constantly available database of individual consumer credit-related activity versus one that allows for time-consuming and complex analytical classifications of consumers, neither model allows the credit provider to make use of newly received information from the last twenty-four hours to identify consumers who are both eligible for a firm offer of credit and are currently interested in obtaining additional credit.
Embodiments of systems and methods are described for automatically analyzing information from an online consumer credit database in order to identify consumers who both meet a credit-provider's criteria for making a firm offer of credit and are also deemed, based on extremely recent indications in the database, known as trigger events, to be currently interested in obtaining credit. The systems and methods further generate timely notifications of the identified prospective customers to the credit-provider. In certain embodiments, the prospect notifications may be generated daily, multiple times per day, or at another advantageous frequency, and may thus more accurately identify consumers who are likely to be currently interested in specific products and/or services.
Systems and methods are described for identifying a subset of interest from a general population and for monitoring a database of daily activity logs associated with the general population in order to identify database entries indicative of an occurrence of a pre-defined trigger event that is associated with a member of the subset of interest. In particular, systems and methods are described that allow a massive database of daily activity logs to be monitored to identify trigger events that have occurred within the past twenty-four hours or other very recent time period. Embodiments are described that may be advantageously used by a provider of credit-related products and/or services who wishes to accurately target prospective customers, identified by the system, based on occurrence of a trigger event, as being in a decision-making phase of credit shopping, for purposes of making a timely and targeted offering relevant to the customers' current activities.
In one embodiment, where clients are entities such as lenders and other providers of credit-related products and services, a subset of the consumer population is identified as meeting a client's set of pre-screen criteria that define, for example, consumers to whom the client would be willing to make a firm offer of credit. Daily credit-related events associated with members of the subset are monitored so that when a pre-determined event, such as a credit-related inquiry, takes place with respect to a member of the subset, the lender is notified and may take a desired action. For example, the lender may wish to present an offer of pre-approved credit to the identified member(s) of the population subset for whom a trigger event has been identified.
An embodiment of an electronic system for providing notifications about credit-related events is described. The system includes: an electronic list of consumers, a database of credit-related information, an electronic set of campaign criteria, and an automated selection system. The electronic list of consumers identifies consumers who have been pre-screened to be eligible for a firm offer of credit. The database of credit-related information includes data about consumers that is updated at least daily to include information about events that have occurred since a last update of the database, wherein the events include events of at least one of the following types: newly-established consumer credit relationships, consumer credit inquiries, and consumer line-of-credit events. The electronic set of campaign criteria describes at least one type of event that is of interest to an entity associated with an offer of credit. The automated selection system is configured to monitor the database at least daily and to identify consumers on the list who are associated with newly-added inquiries or new credit relationships which are of the at least one type of event described in the set of campaign criteria. In some embodiments, the system includes a prospect list generation system that receives a list of the consumers identified each day by the selection system and that makes the list available to the entity associated with the offer of credit.
An embodiment of a computer-implemented method of providing notifications about credit-related occurrences is described. The method comprises: (a) obtaining an electronic list of consumers who meet a set of pre-screen criteria for an offer of credit; (b) monitoring a database of consumer credit-related events to identify credit-related occurrences associated with one or more consumers on the list, wherein the occurrences have been added to the database within a time period of interest; and (c) providing a notification of the consumers associated with the identified credit-related occurrences.
An embodiment of a method of providing notifications about credit-related events is described. The method includes obtaining a list of names of consumers who meet a set of pre-screen criteria for a credit offer and receiving information that identifies one or more types of credit-related events as indicating that a consumer is currently interested in obtaining credit. The method further includes monitoring a database of consumer credit-related events that is updated at least daily to identify credit-related events associated with one or more names on the list, wherein the events have been added to the database within a time period of interest, and providing a notification of the names associated with the identified credit-related events.
An embodiment of a system for providing notifications about credit-related events is described. The system includes: a pre-screen list generation system, a database of credit-related information about consumers, a set of campaign criteria, and a prospect list generation system. The pre-screen list generation system is configured to receive from a credit-provider a set of eligibility criteria. The pre-screen list generation system is further configured to use the eligibility criteria to identify consumers listed in a consumer database who are eligible for a firm offer of credit from the credit-provider and to generate a pre-screen list of the identified names. The database of credit-related information about consumers is updated at least daily to include information about events that have occurred since a last update of the database, wherein the events include newly-established consumer credit relationships and inquiries about a consumer's credit score. The set of campaign criteria describes at least one type of event that is of interest to the credit-provider as being indicative of a consumer's current interest in obtaining credit. The selection system is configured to monitor the database and capture results at least daily and to identify consumers on the pre-screen list who are associated with one or more events that have been added to the database since a last monitoring, the events being of a type described in the campaign criteria. The prospect list generation system receives a list of the consumers identified each day by the selection system and makes the list available to the entity wishing to offer credit.
Neither this summary nor the following detailed description defines or limits the invention. The invention is defined by the claims.
A general architecture that implements various features of specific embodiments of the invention will now be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention.
The following description discloses several embodiments of a computer-implemented system for automatically analyzing large quantities of credit-related consumer data on a daily or other frequent basis in accordance with processing instructions that are customized to suit a client's promotional campaign. In a preferred embodiment, the system is configured to generate a daily list (or multiple lists per day) of consumer names and related data useful for efficiently executing an advertising campaign based on recent inputs to a database of consumer activity.
However, if the credit-provider is able to identify one or more consumer activities that signal a greater likelihood of interest in obtaining credit on the part of a consumer who is in the market for credit, and if the credit-provider is able to receive timely information about the occurrence of such consumer activities, then the credit-provider can more effectively make use of resources expended during a promotional campaign by targeting consumers identified as having recently been involved in such activities. In other words, automatic recognition of an occurrence of such an identified consumer activity may serve as a trigger to notify a credit-provider or other interested party that an identified consumer is currently a good prospect for their promotional offer.
A computer system that is capable of processing massive quantities of data with the speed needed to identify daily triggers provides an important informational advantage to a credit-provider or other client of the system. A credit-provider may possess such a computer system, or, more frequently, may become a client of a business entity that has access to massive computer resources and to credit-related information and that offers such daily prospect trigger notifications.
Current government regulations that protect consumers from unwarranted financial surveillance and from unfair use of personal information may impose additional restrictions on the computer-implemented system for providing daily notifications based on prospect triggers notifications. For example, current federal regulations require that a firm offer of credit must be extended to every consumer whose name is included in a file that is generated by monitoring daily credit-related consumer activities. In order to be of commercial value to credit-providers, while at the same time complying with government regulations, the computer-implemented prospect trigger notification system first analyzes stored consumer data, which is frequently about consumers with whom the credit-provider does not currently have a business relationship, in order to exclude those consumers who do not meet a set of criteria that define consumers to whom the client is willing to extend a firm offer of credit.
As depicted in
The online database 120 may be implemented using one or more mainframe computers, mini-computers, personal computers configured as a server farm, or other suitably configured set of computers with sufficient storage and processing capacities.
In a preferred embodiment, the online database 120 is configured as a relational database comprising a plurality of tables, as will be described in greater detail with reference to
Information from the online database 120 is processed and used to generate a data warehouse 130 for a population of consumers. The information may represent a “snapshot” of the information in the online database 120 and may be periodically updated, such as monthly, weekly, twice weekly, or according to another desired schedule. The data warehouse 130 may process the data from the online database 120, and may include additional data not found in the online database 120, in order to facilitate in-depth analysis of the data for a variety of credit-related and other purposes without disturbing normal functioning of online database 120. For example, some or all of the data from the online database 120 may be verified for accuracy before being entered into the data warehouse 130. Additional information associated with individual consumers, such as demographic information, employment information, and other information of interest for credit-related purposes may be added to the data warehouse 130.
In a preferred embodiment, the data warehouse 130 is implemented as a relational database, although data in the data warehouse 130 may be organized differently than data in the online database 120. The data warehouse 130 may be implemented using one or more mainframe computers or other suitably configured set of computers with sufficient storage and processing capacities. Furthermore, although the online database 120 and the data warehouse 130 have each been depicted in
One embodiment of the data warehouse 130 is described in the co-owned and co-pending U.S. patent application Ser. No. 11/103,659, filed on Apr. 11, 2005, and entitled SYSTEMS AND METHODS FOR OPTIMIZING DATABASE QUERIES, the disclosure of which is hereby incorporated herein by reference in its entirety.
As described above, a client 160 may be a business entity that wishes to undertake a sales campaign or other promotional activity. In order to generate a list of consumers with whom a credit-provider does not currently have a business relationship, but to whom the credit-provider is willing to make a firm offer of credit, a sub-population of interest is identified from the records of the data warehouse 130. In some embodiments, the sub-population of interest may be identified in order to generate a list of existing customers with whom a new credit relationship is desired.
For example, in a preferred embodiment, the client identifies a set of “pre-screen” criteria that define consumers who qualify for a firm offer of credit, such as for a car, home equity or other type of loan from the client. To continue the example, the client's pre-screen criteria may specify that consumers with credit ratings above a threshold value and who have had no repossessions on automobile loans are eligible for a firm offer of credit on an automobile loan. More frequently, clients may wish to specify pre-screen criteria that are much more complex in order to identify a desired target sub-set of the population.
Applying the client's pre-screen criteria to records in the data warehouse 130 generates a subset list 140 that includes a subset of consumer names from the data warehouse 130, for example, fifty million consumers out of two hundred and thirty million, who meet the client's pre-screen criteria. The subset list 140 may be regenerated monthly, or bi-weekly, or according to another periodic or other type of schedule, and may be based on an updated set of pre-screen criteria provided by the client 160. In some jurisdictions, government regulations require that pre-screen lists 140 be updated at a minimum frequency or more, such as at least every thirty or ninety days, in order to ensure that consumers are being selected for credit or other types of offers based on credit-related data that is current.
The trigger notification system 100, which is preferably implemented as a software package that is configured to run on general purpose computer equipment and to access records within the online database 120, receives a copy of a client's pre-screen subset list 140 and a set of one or more trigger events 146 of interest to the client 160. A trigger event is typically an event or occurrence that is logged in the online database 120 of daily consumer activities and that the client 160 wishes to use to identify consumers who may be actively shopping for specific products and/or services. For example, an inquiry regarding a consumer's credit score from a home mortgage provider may be an indication that the consumer is actively shopping for a mortgage. The trigger notification system 100 uses the subset list 140 and the client-provided set of trigger events 146 to monitor updates to the daily credit-related activity database 120 that are associated with consumers included in the pre-screen subset list 140.
A business entity that operates the trigger notification system 100 preferably serves many different clients 160, each interested in conducting its own promotional campaign(s), with its own pre-screen criteria and resultant subset list 140, as well as each with its own set of trigger events 146 and other campaign-related instructions. For ease of description, however, the descriptions of the systems and methods provided herein frequently refer to the client 160 in the singular. It will be appreciated that the business entity operating the trigger notification system 100 may provide the services described herein to a plurality of clients 160 at the same time.
The trigger notification system 100 monitors updates to the online database 120 associated with consumers on the subset list 140, as is described in greater detail with reference to
The trigger notification system 100 compiles a list 150 of consumers from the subset list 140 whose associated records in the online database 120 indicate a current trigger event. The trigger notification system 100 preferably provides the client 160 with a daily, or more frequent, list of names 150 triggered within a recent short period of time, such as within the last twenty-four hours, so that the client 160 may quickly make use of the information that the identified consumers are currently good prospects for an offer of credit. In various embodiments, if requested by the client, the daily list of triggered names 150 may include, in addition to consumer names, identification of the one or more trigger events that occurred with respect to each consumer, as well as other identifying and/or contact information for the consumers on the list 150.
In some jurisdictions, legal regulations may further stipulate that, along with the daily list of triggered names 150, the trigger notification system 100 provides the client 160 with a consumer statement file, containing consumer statements of explanation associated with the contents of their credit files for any consumers included on the daily list of triggered names 150.
If requested by the client 160, the trigger notification system 100 may filter, sort, or otherwise modify the daily list of triggered names 150. For example, if a client 160 requests monitoring of more than one event trigger for the trigger notification system 100 to monitor, the trigger notification system 100 may group the identified consumer names 150 by the associated trigger. In situations where a given consumer is associated with more than one trigger event on the same day, the trigger notification system 100 may list the consumer in all appropriate groups or may list the consumer in only one group. For example, the client 160 may identify a hierarchy or other prioritized list of the trigger events and may request that triggered consumers be listed only with the trigger event of highest rank with which the consumer is associated on that day.
As another example, the client 160 may request that the trigger notification system 100 filter the daily set of triggered consumer names to exclude or identify a consumer who is repeatedly associated with a same trigger events within a given time span. For example, the client 160 may request that the trigger notification system 100 include the consumer's name in the daily list 150 only once or only once per week for a given trigger. Thus, if the online database 120 includes multiple inquiries associated with car loans for a given consumer over the span of two weeks, the consumer's name may appear on the daily list of triggered names 150 only the first time.
Furthermore, the client 160 may request that the trigger notification system 100 limit the daily list of triggered names 150 to only a pre-determined number of names, such as, for example, if the client 160 does not have the capacity to contact or otherwise make use of the full set of names in a timely manner. These and other modifications to the operation of the trigger notification system 100 will be appreciated by a skilled artisan as being within the scope of the invention as described herein.
In some embodiments, the client 160 communicates with the trigger notification system 100 via computer network, such as the Internet, and may be provided with a secure user interface, such as one or more web pages of a secure website that allow the client to input and/or modify triggers for use by the trigger notification system 100. In some embodiments, the client 160 may additionally or alternatively use a secure user interface, such as one or more web pages of a secure website to input and/or update the pre-screen criteria.
In some embodiments, the client 160 may also receive the daily list of triggered names 150 via secure Internet connection. In other embodiments, the client 160 and the trigger notification system 100 may communicate using T-1 or T-3 lines, or other dedicated or non-dedicated high-speed communications lines. Alternatively, clients 160 and the trigger notification system 100 may communicate using other data transmission systems and protocols. For example, clients 160 may receive their daily list of triggered names 150 as a text document or as a comma-delimited file transport protocol (FTP) transmission that may be downloaded into a spreadsheet application. In some embodiments, a portion of the communications between the client 160 and the trigger notification system 100 may be conducted in person, in writing, via telephone, or using other communication methods.
In some embodiments, the client 160 may provide a list of prospect names 145 for use by the trigger notification system 100. For example, the client 160 may provide a list 145 of current customers for whom the client 160 would like to identify additional credit relationship possibilities using the trigger notification system 120. As another example, the client 160 may provide a list 145 of consumers who have recently contacted them with credit-related questions but who have not entered into any business relationship with the client 160. As a third example, the client 160 may provide a list 145 that the client has purchased or otherwise acquired from another vendor. The trigger notification system 100 may use the client-provided list of prospect names 145 in addition to or as an alternative to the pre-screen subset list 140 as the list of names for whom triggered monitoring of the online database 120 is requested.
Government and other regulations may specify that consumers who wish not to be contacted for advertising purposes must be left off of contact lists generated for advertising purposes. In some jurisdictions, such consumers may express their desire by adding their name to an “opt-out/pander list” of people explicitly requesting not to be contacted with advertising offers. In various embodiments of the systems and methods described herein, verifying that such consumer names do not appear on the daily list of triggered names 150 supplied to the client 160 may be carried out by the trigger notifications system 100 and/or as part of the generation of the pre-screen subset list 140. Similarly, compliance with other regulations and legal requirements may be carried out by the trigger notification system 100 and/or by other components described herein.
In addition to or as an alternative to event-based triggers, the client 160 may identify other types of trigger occurrences of interest that may appear in the records of the online database 120. For example, the client 160 may be interested in identifying consumers whose credit balance is within a given amount or percentage of their credit limit or whose debt ratio has reached a threshold value. The client 160 may be interested in identifying consumers whose credit score has changed in value by a certain number of points or by a pre-determined percentage within a given time. Furthermore, in some embodiments, the client 160 may categorize consumers according to “credit score bands,” to which they belong by virtue of their credit score, such that a consumer may belong to the “600-650” band or to the “650-700” band based on their credit score. In such embodiments, the client 160 may wish to be notified of consumers who have moved from one credit score band to another within the last twenty-four hours or other recent period.
In some embodiments, information obtained as a result of the trigger notifications system's 100 monitoring of the online database 120 may be used as an input to an automated decisioning or learning system, in addition to or as an alternative to being used to provide the client 160 with a daily list of triggered names 150. In such embodiments, the automated decisioning or learning may be carried out by the trigger notification system 100 or another system component in communication with the trigger notification system 100 or by the client 160 or by another entity associated with the client 160, or by a combination of the above.
For example, in one embodiment, the clients 160 provide feedback data to the trigger notification system 100 regarding the success rates of their consumer contact campaigns that are based on trigger notifications 150. The feedback data provided by a given client 160 is preferably time-stamped or segmented to permit the success rate information to be correlated with the trigger criteria, and possibly with the pre-screening criteria, used by that client 160 to generate the associated list or lists of prospects 150. A software-based analysis component of the trigger notification system 100 analyzes the collected feedback data, collectively and/or on a client-specific basis, to identify the trigger criteria, and optionally the pre-screen criteria, that produces the “best” results (e.g., the highest success rate, as measured based on the percentage of the contacted prospects that accept the associated offer from the client).
Results of this analysis may be disseminated to the clients 160 via auto-generated, periodic reports to assist the clients 160 in modifying their trigger criteria and/or pre-screen criteria over time so as to improve their respective success rates. The reports may, for example, separately identify, for each of a plurality of different products and services, those criteria that tend to produce the highest success rates, as determined based on a collective analysis of all the feedback data and associated criteria settings of many different clients (e.g., tens to hundreds of different clients). The reports may also include client-specific recommendations based on the feedback data provided by the particular client.
The business entity that operates the trigger notification system 100 may also provide a computer-implemented service for enabling clients to request and obtain mutually exclusive lists of prospects, such that two competing clients 160 will not be notified of the same prospect at the same time. This feature may, for example, be implemented using a round robin protocol in which each time a consumer matches the trigger criteria of multiple competing clients, that consumer is added only to the prospect list of the next client in sequence. This feature, which may be implemented within the software of the trigger notification system 100, can significantly increase the success rates of the clients' campaigns, while reducing the likelihood that the consumers will be overwhelmed by the volume of contacts made by clients 160.
A consumer table 127 of the consumer activity database 120 includes identifying and other personal information for each consumer in the database 120. The consumer's record may include, by way of example, the consumer's PIN and full legal name, driver's license information, and the like.
A trade table 121 stores information about existing credit card relationships associated with each consumer. For example, in
An inquiry history table 122 stores information about credit score inquiries that have been submitted to the online database 120. For example, in
An address table 123 stores information about known addresses, which may be indexed by an Address Identification Number (AIN), that are associated with consumers.
A public records table 126 stores information about consumers that may be relevant to a consumer's credit rating and that is typically available to the public. For example, information about bankruptcies, liens, property titles, and the like may be stored in the public record table 126. An employment table 125 stores information about a consumer's employment history. In other embodiments, other tables may be additionally or alternatively used to store data about the consumers' credit-related activities.
As depicted in
A pre-screen list 230 of consumers who meet a client's criteria for a firm offer of credit is obtained for each client campaign. As was described with reference to
For efficiently serving many clients 160 simultaneously, the trigger notification system 100 may compile a master pre-screen list 240 that may be compiled from the various campaign pre-screen lists 220 received from the clients 160. The master pre-screen list 240 advantageously takes into account the fact that a given consumer may meet the campaign criteria for more than one client and/or for more than one campaign. Thus, by combining the various campaign pre-screen lists 220, the trigger notification system 100 is able to more efficiently monitor the daily credit-related occurrence information 210 received from the online database 120 and to provide the list of prospect triggered names 150 to clients 160 in a timely, preferably daily, schedule. An example of a master pre-screen list 240 is described in greater detail with reference to
The trigger notification system 100 receives information about daily credit-related occurrences 210 that were reported to and logged in the online database 120. In a preferred embodiment, the online database 120 receives information about credit-related activities around-the-clock and seven-days-a-week. In general, client campaigns that make use of prospect triggers are especially interested in credit-related inquiries associated with a given consumer. For example, the client may wish to be notified when information in the database 120 indicates that the consumer has made an inquiry about a home equity loan, a car loan, or a mortgage. However, some campaigns may be interested in events such as credit balance changes, and the like.
Information about inquiries newly-logged in the database 120 may be provided to the selection system 200 of the trigger notification system 100 once daily or at more frequent intervals. When the daily occurrences information 210 is provided to the trigger notification system 100 two or more times during the day, the selection system 200 may process the available portion of the incoming occurrence information 210 at various times throughout the day, and may provide the information to the prospect list generation system 260, in order to compile a daily prospect trigger list 150, as will be described in greater detail below.
In one simple embodiment, the selection system 200 simply collects information about credit inquiry occurrences associated with consumers on the master pre-screen list 240, and sends the information to the prospect list generation system 260 for separation according to individual client campaigns and for transmission to the appropriate clients 160. In another embodiment, the prospect list generation system 260 simply forwards a list received from the selection system 200 to an applicable client. The prospect list generation system 260 may also send a record to the historical log 270 of the list 150 that was sent to the client 160, as will be described in greater detail with reference to
In other preferred embodiments, the selection system 200 accesses additional information before forwarding the triggered consumer names and other information to be sent to the client, in order to provide additional screening of the occurrence information 210. This additional processing may advantageously provide additional assurance that the list of consumer names 150 sent to client 160 contains only bona fide qualified consumers, which is of especial advantage to clients in jurisdictions in which government regulations specify that every consumer whose name is received by the client 160 on a prospect trigger list 150 must be extended a firm offer of credit.
In various embodiments, therefore, the selection system 200 receives further information about client campaign criteria 220, about consumer opt-out/pander lists 250 and/or the historical log 270 of previous trigger notifications sent to clients 160 for a given consumer.
The opt-out/pander list 250 includes the names of consumers who have specifically requested that they not be contacted with advertisements of various types, including credit-related offers. In some jurisdictions, consumers may register with one or more government programs that maintain consumer opt-out/pander lists 250. Government agencies may further undertake to enforce compliance with the opt-out/pander lists 250 by levying fines on businesses that contact consumers on the list(s). Although opt-out/pander lists 250 are frequently consulted in compiling a client's original campaign pre-screen list 220, clients may request that consumers on a given day's prospect trigger list be again compared to the opt-out/pander lists 250, in part to verify that the consumer has not been placed on the opt-out/pander list 250 since the campaign pre-screen list 220 was compiled. Consumers whose names appear on the master pre-screen list 240, who are associated with a daily trigger, and who are identified by the selection system 200 as appearing on an opt-out/pander list 250, will frequently be removed from the daily prospect list 150 before the list 150 is sent to the client 160.
As has been described above, clients 160 may also specify additional types of campaign-specific criteria 220 to be applied to consumers associated with daily occurrences that serve to filter the daily set of prospect triggers being compiled by the trigger notification system 100. For example, because a client's pre-screen list 230 is frequently regenerated only monthly or even quarterly, some consumer data of interest to the client 160 may have changed in the interim, and the client may wish to have critical data re-verified before a consumer's name is placed on the daily prospect trigger list 150 that will be supplied to the client 160. For example, a client 160 may wish to have one or more of the consumer's credit scores re-calculated using up-to-date information before being sent the consumer's name and contact information.
Furthermore, in an effort to avoid creating a negative impression for a consumer by making multiple offers of the same credit product or service within a short time period, a client may specify that a consumer who has been contacted by the client based on a prospect trigger notification should not be included on another prospect triggers list 150 for a specified period of time, such as for thirty, sixty, or ninety days. Such a period of non-contact may be known as a “cool-off” period. The selection system 200 may consult the historical log 270 of notification triggers activity to determine if the consumer is still within a cool-off period based on a previous contact by the client.
The selection system 200 may also receive additional information from the client 160 as part of the client campaign criteria 220. For example, in additional to information about the trigger events about which the client is interested, the client may send information about any desired hierarchy of campaigns, such that a consumer for whom a trigger event is identified for more than one campaign, may be put on a list of triggered names 150 for a campaign with a higher ranking and not put on a list 150 for a campaign with a lower ranking. For example, a client who is a credit card provider may instruct the trigger notification system 100 to implement a hierarchy that includes a rule stipulating: if a pre-screened consumer is triggered for a “Platinum Card” campaign and for a “Gold Card” campaign, put the consumer name on the “Platinum Card” list only.
The campaign criteria 220 may also include a request to append additional data to each consumer name included on the trigger notification list 150, as will be described in greater detail with reference to
Once the selection system 200 has processed the information 210, 220, 240, 250, 270, the selection system 260 sends the resulting data to the prospect list generation system 260 for further processing and for generating the individual lists of triggered names 150 for making available to the clients 160.
Thus, the master pre-screen list 240 forms a master list of consumers for whom the trigger notification system 100 is requested to monitor daily credit-related occurrences 210.
As depicted in
In some embodiments, the client 160 may request that the business entity offering the prospect trigger notification service also generate the pre-screen list 220 of consumers that match the client's specified criteria. As was described with reference to
Alternatively or additionally, the client 160 may generate, purchase, or otherwise acquire a list 145 of consumers that are deemed to be acceptable for a firm offer of credit and may provide the list 145 for use by the trigger notification system 100.
In Block 620, a master pre-screen list 240 is created for use by the trigger notification system 100. The master pre-screen list 240 combines information from a plurality of client campaign pre-screen lists 230, as exemplified in the sample master pre-screen list of
In Block 630, the trigger notification system 100 receives the list of new occurrences 210 that have been reported and entered into the online database 120 within a recent period of time, such as within the last day. A simplified example of a daily occurrences list 210 is depicted and described with reference to
In Block 640, the selection system 200 of the trigger notification system 100 filters the list of daily occurrences 210 to identify, for each client campaign, the consumers who (a) meet the client's pre-screen criteria, (b) are associated with a trigger event of interest to the client that occurred within a recent time period of interest to the client, and (c) also meet any additional criteria 220 for the campaign that has been specified by the client, as was described with reference to
In some embodiments, as has been described with reference to
Once the triggered consumer names have been filtered according the client's campaign criteria 220, the daily list of prospect triggered names 150 may be compiled by the prospect list generation system 260, together with any appended data 220 requested by the client, and sent, or otherwise made available, to the client 160. The prospect list generation system 260 may also notify the historical log 270 of the list of triggered names 150 sent to the client.
The process 640, as depicted in
If the consumer name is not on an opt-out/pander list 250, the process move to Block 642, where consumer names that are not on the client's pre-screen list for the campaign are deleted from, or not included in the list of triggered names 150 for the campaign.
In Block 643, any campaign-specific criteria 220 with regard to campaign hierarchies or “cool-off” periods provided by the client is used to further process the daily list of occurrences 210. For example, if the consumer name has already been added to a list 150 for a campaign with a higher ranking in the provided hierarchy of campaigns, the consumer name may be deleted, in Block 646, from the list 150 for any lower-ranking campaign of the client's. As another example, if information from the historical log 270 indicates that the consumer's name has been put on a prospect trigger list 150 within a recent period designated by the client as a “cool-off” period for the campaign, then the selection system 200 may, in Block 646, delete the consumer name from the list of triggered names 150 for this campaign.
In Block 644, the selection system 200 may check the consumer's trigger event with regard to one or more additional filters provided with the campaign criteria 220. For example, the client's credit score, address information, or employment information may be re-checked for accuracy.
If this occurrence of a trigger event for the consumer passes all of the above tests, in Blocks 641-644, then the consumer name for this trigger event may be included in a processed version of the list of triggered names 150 for the campaign.
As noted above, in various embodiments, the process 640 may be carried out, in whole or in part, by the selection system 200 and/or by the prospect list generation system 260. Thus, although the process 640 is described as being carried out by the selection 200, various embodiments of the trigger notification system 100 may carry out the functions of the process 640 in a variety of different ways.
Although the foregoing systems and methods have been described in terms of certain preferred embodiments, other embodiments will be apparent to those of ordinary skill in the art from the disclosure herein. On a very basic level, although many of the lists, repositories, and various data sets have been described herein as including consumer names, it will be readily apparent to one of skill in the art that the lists, repositories, various data sets and other applicable components, may be alternatively and even preferably implemented using one or more identifiers for the consumers other than their names. As another example, while the embodiments described herein have been described with respect to an online database 120 and a data warehouse 130, in other embodiments, the two databases 120, 130 may be implemented as a single database configured to provide the functionality described herein with reference to the online database 120 and the data warehouse 130. Furthermore, while the trigger notification system 100 has been described as monitoring updates to the online database 120, in other embodiments the trigger notification system 100 additionally or alternatively monitors updates to the data warehouse 130. Additionally, other combinations, omissions, substitutions and modifications will be apparent to the skilled artisan in view of the disclosure herein. While certain embodiments of the inventions have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms. Accordingly, the accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the invention.
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|Classification aux États-Unis||705/14.1|
|Classification internationale||G06Q30/00, G06Q90/00|
|Classification coopérative||G06Q90/00, G06Q30/0251|
|9 févr. 2006||AS||Assignment|
Owner name: EXPERIAN INFORMATION SOLUTIONS, INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:RAMOS, ARMANDO;REEL/FRAME:017248/0020
Effective date: 20060113
Owner name: EXPERIAN INFORMATION SOLUTIONS, INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:MEEKS, STEPHEN R.;BODDA, MICHELE M.;FIELDING, PAMELA;REEL/FRAME:017248/0008
Effective date: 20060125